First Order Methods for Optimization on Riemannian Manifolds (Q3300552)

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Language	Label	Description	Also known as
English	First Order Methods for Optimization on Riemannian Manifolds	scientific article

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scholarly article

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First Order Methods for Optimization on Riemannian Manifolds (English)

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Maurício Silva Louzeiro

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Orizon P. Ferreira

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Handbook of Variational Methods for Nonlinear Geometric Data

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publication date

29 July 2020

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describes a project that uses

Matrix Means Toolbox

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MaRDI profile type

MaRDI publication profile

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full work available at URL

https://doi.org/10.1007/978-3-030-31351-7_18

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Trust-region methods on Riemannian manifolds

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On the Convergence of Gradient Descent for Finding the Riemannian Center of Mass

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Geometric Means in a Novel Vector Space Structure on Symmetric Positive‐Definite Matrices

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The proximal point algorithm in metric spaces

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A Second Order Nonsmooth Variational Model for Restoring Manifold-Valued Images

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Enlargement of monotone vector fields and an inexact proximal point method for variational inequalities in Hadamard manifolds

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A subgradient method for multiobjective optimization on Riemannian manifolds

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Finite termination of the proximal point method for convex functions on Hadamard manifolds

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Subgradient method for convex feasibility on Riemannian manifolds

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Proximal point method for a special class of nonconvex functions on Hadamard manifolds

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A new approach to the proximal point method: convergence on general Riemannian manifolds

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Iteration-complexity of gradient, subgradient and proximal point methods on Riemannian manifolds

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Computing Riemannian center of mass on Hadamard manifolds

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A second-order TV-type approach for inpainting and denoising higher dimensional combined cyclic and vector space data

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A Parallel Douglas–Rachford Algorithm for Minimizing ROF-like Functionals on Images with Values in Symmetric Hadamard Manifolds

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Statistics on Riemannian manifolds: asymptotic distribution and curvature

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Computing the Karcher mean of symmetric positive definite matrices

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Stochastic Gradient Descent on Riemannian Manifolds

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Global rates of convergence for nonconvex optimization on manifolds

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Total Generalized Variation for Manifold-Valued Data

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Full convergence of the steepest descent method with inexact line searches

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On the proximal point method in Hadamard spaces

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Proximal point algorithms involving fixed points of nonexpansive mappings in \(\mathrm{CAT}(0)\) spaces

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Convergence of some algorithms for convex minimization

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On solving the minimization problem and the fixed-point problem for a finite family of non-expansive mappings in CAT(0) spaces

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Contributions to the study of monotone vector fields

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Convex- and monotone-transformable mathematical programming problems and a proximal-like point method

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The Geometry of Algorithms with Orthogonality Constraints

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Subgradient algorithm on Riemannian manifolds

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Proximal Point Algorithm On Riemannian Manifolds

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Gradient Method for Optimization on Riemannian Manifolds with Lower Bounded Curvature

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Iteration-complexity of the subgradient method on Riemannian manifolds with lower bounded curvature

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Geodesic regression and the theory of least squares on Riemannian manifolds

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Minimizing a differentiable function over a differential manifold

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Subgradient optimization in nonsmooth optimization (including the soviet revolution)

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\(\varepsilon\)-subgradient algorithms for locally Lipschitz functions on Riemannian manifolds

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Analysis Operator Learning and its Application to Image Reconstruction

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A Broyden Class of Quasi-Newton Methods for Riemannian Optimization

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A survey and comparison of contemporary algorithms for computing the matrix geometric mean

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Resolvents of convex functions in complete geodesic metric spaces with negative curvature

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Incremental gradient method for Karcher mean on symmetric cones

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Iterative approaches to solving convex minimization problems and fixed point problems in complete CAT(0) spaces

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An abstract proximal point algorithm

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Variational Inequalities for Set-Valued Vector Fields on Riemannian Manifolds: Convexity of the Solution Set and the Proximal Point Algorithm

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Monotone vector fields and the proximal point algorithm on Hadamard manifolds

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Weak Sharp Minima on Riemannian Manifolds

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The Gradient Projection Method Along Geodesics

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A framework for generalising the Newton method and other iterative methods from Euclidean space to manifolds

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Newton methods for nonsmooth convex minimization: connections among \(\mathcal U\)-Lagrangian, Riemannian Newton and SQP methods

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On the Riemannian geometry defined by self-concordant barriers and interior-point methods.

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Proximal point algorithms for solving convex minimization problem and common fixed points problem of asymptotically quasi-nonexpansive mappings in CAT(0) spaces with convergence analysis

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Steepest descent method with a generalized Armijo search for quasiconvex functions on Riemannian manifolds

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Modified proximal point algorithms for solving constrained minimization and fixed point problems in complete CAT(0) spaces

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Smooth nonlinear optimization of \(\mathbb R^n\)

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Monotone Operators and the Proximal Point Algorithm

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Domains of positivity

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Riemannian Gaussian Distributions on the Space of Symmetric Positive Definite Matrices

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A Dai-Yuan-type Riemannian conjugate gradient method with the weak Wolfe conditions

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Optimization Techniques on Riemannian Manifolds

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A proximal point algorithm for DC functions on Hadamard manifolds

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Conic Geometric Optimization on the Manifold of Positive Definite Matrices

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A hybrid proximal point algorithm for finding minimizers and fixed points in CAT(0) spaces

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Convergence of Newton's method for sections on Riemannian manifolds

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Subgradient algorithms on Riemannian manifolds of lower bounded curvatures

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Monotone and accretive vector fields on Riemannian manifolds

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Linear Convergence of Subgradient Algorithm for Convex Feasibility on Riemannian Manifolds

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Proximal Point Algorithms on Hadamard Manifolds: Linear Convergence and Finite Termination

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Equilibrium problems on Riemannian manifolds with applications

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Total Variation Regularization for Manifold-Valued Data

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Mumford-Shah and Potts regularization for manifold-valued data

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A feasible method for optimization with orthogonality constraints

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A Riemannian variant of the Fletcher-Reeves conjugate gradient method for stochastic inverse eigenvalue problems with partial eigendata

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A Majorization-Minimization Algorithm for Computing the Karcher Mean of Positive Definite Matrices

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An incremental subgradient method on Riemannian manifolds

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A Riemannian conjugate gradient method for optimization on the Stiefel manifold

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Identifiers

10.1007/978-3-030-31351-7_18

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Mathematics Subject Classification ID

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zbMATH DE Number

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Sitelinks

Mathematics(1 entry)

mardi Publication:3300552

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